Royal Institute of Philosophy Public Lecture - Prof Seumas Miller - Predictive Policing: The Ethical Issues

The topic of this public lecture is the ethical issues in predictive policing (i.e., the use of crime mapping data and analysis, social network analysis, big data and predictive algorithms in crime fighting, some of which are predicted in the film Minority Report). 

Professor Seumas Miller (Distinguished Research Fellow at the Oxford Uehiro Centre for Practical Ethics) discuses Predictive policing (PP)

PP is a term that refers to a range of crime-fighting approaches that use crime mapping data and analysis, social network analysis, big data and predictive algorithms. The rise of PP, such as in Los Angeles, Chicago and New York, has raised the spectre of the surveillance society, described in the film, Minority Report, in which citizens can be arrested by police for crimes they have not yet committed (and have no intention of committing at the time of arrest) on the basis of (supposedly reliable) evidence that they will commit them. Perhaps these fears are misplaced, however PP and the technologies that it does or could rely on raises a number of important ethical issues. For instance, one of the more controversial predictive policing techniques is profiling, which can take the form of morally problematic racial profiling. Again, the capacity to integrate databases of biometric and non-biometric information - such as smart phone and email metadata, financial, medical and tax records – is a major ethical concern. Consider that biometric facial image templates can be used in conjunction with digital images sourced from CCTV, phone GPS data, and internet history, to provide an increasingly complete picture of an individual’s movements and lifestyle. Privacy and confidentiality in relation to personal data consists in large part in the right to control access to, and use of, that data. As such, it is a component of individual autonomy, a cornerstone of liberal democracy.

Event contact: michael.wilby@aru.ac.uk